• DocumentCode
    780141
  • Title

    Melody Transcription From Music Audio: Approaches and Evaluation

  • Author

    Poliner, Graham E. ; Ellis, Daniel P W ; Ehmann, Andreas F. ; Gómez, Emilia ; Streich, Sebastian ; Ong, Beesuan

  • Author_Institution
    Dept. of Electr. Eng., Columbia Univ., New York, NY
  • Volume
    15
  • Issue
    4
  • fYear
    2007
  • fDate
    5/1/2007 12:00:00 AM
  • Firstpage
    1247
  • Lastpage
    1256
  • Abstract
    Although the process of analyzing an audio recording of a music performance is complex and difficult even for a human listener, there are limited forms of information that may be tractably extracted and yet still enable interesting applications. We discuss melody-roughly, the part a listener might whistle or hum-as one such reduced descriptor of music audio, and consider how to define it, and what use it might be. We go on to describe the results of full-scale evaluations of melody transcription systems conducted in 2004 and 2005, including an overview of the systems submitted, details of how the evaluations were conducted, and a discussion of the results. For our definition of melody, current systems can achieve around 70% correct transcription at the frame level, including distinguishing between the presence or absence of the melody. Melodies transcribed at this level are readily recognizable, and show promise for practical applications
  • Keywords
    audio recording; music; audio recording; melody transcription; music audio; Application software; Audio recording; Data mining; Digital recording; Digital signal processing; Frequency estimation; Humans; Information analysis; Instruments; Performance analysis; Audio; evaluation; melody transcription; music;
  • fLanguage
    English
  • Journal_Title
    Audio, Speech, and Language Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1558-7916
  • Type

    jour

  • DOI
    10.1109/TASL.2006.889797
  • Filename
    4156215